PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Improved answer ranking in social question-answering portals
Felix Hieber and Stefan Riezler
In: 3rd International Workshop on Search and Mining User-generated Contents (SMUC 2011), Glasgow, Scotland, UK(2011).

Abstract

Community QA portals provide an important resource for non-factoid question-answering. The inherent noisiness of user-generated data makes the identication of high-quality content challenging but all the more important. We present an approach to answer ranking and show the usefulness of features that explicitly model answer quality. Furthermore, we introduce the idea of leveraging snippets of web search results for query expansion in answer ranking. We present an evaluation setup that avoids spurious results reported in earlier work. Our results show the usefulness of our features and query expansion techniques, and point to the importance of regularization when learning from noisy data

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
ID Code:8490
Deposited By:Sebastian Pado
Deposited On:16 February 2012